Tesseract vs EasyOCR: Which One to Choose for Your OCR Needs?
Tesseract vs EasyOCR
Which One to Choose for Your OCR Needs?
Optical Character Recognition (OCR) is a crucial technology for extracting text from images and scanned documents. Among the many OCR tools available, Tesseract OCR and EasyOCR are two popular choices. But which one is the right fit for your project? Let’s dive into a detailed comparison of their features, performance, and use cases.
1. Introduction to Tesseract and EasyOCR
Tesseract OCR
Tesseract, originally developed by HP and now maintained by Google, is an open-source OCR engine. It is widely used in various applications due to its accuracy and language support.
Key Features:
Supports over 100 languages
Works well with structured text (printed documents, PDFs)
Free and open-source
Can be integrated with Python via
pytesseractWorks best with preprocessed, high-quality images
Supports multiple page segmentation modes (PSM) for different text structures
Offers various configuration parameters for tuning OCR performance
EasyOCR
EasyOCR, developed by the Jaided AI team, is a deep-learning-based OCR library. It is designed for quick and easy integration, making it a strong competitor to Tesseract.
Key Features:
Supports over 80 languages, including complex scripts like Chinese and Hindi
Uses deep learning models for better text detection in noisy images
Faster processing time compared to Tesseract
Simple Python API for easy integration
Works well with handwritten text and low-quality images
Customizable parameters for better accuracy and control
2. Performance Comparison
Accuracy
| Feature | Tesseract OCR | EasyOCR |
|---|---|---|
| Printed Text | High Accuracy | High Accuracy |
| Handwritten Text | Low Accuracy | Better Accuracy |
| Noisy Images | Struggles without preprocessing | Handles well with deep learning |
| Multilingual Support | Over 100 languages | Over 80 languages |
Speed
Tesseract: Slower, especially with larger documents.
EasyOCR: Faster due to deep learning optimizations.
Ease of Use
Tesseract requires additional preprocessing steps for best results.
EasyOCR works well out-of-the-box with minimal preprocessing.
3. Tesseract and EasyOCR Parameters
Tesseract OCR Parameters
Tesseract allows customization using various parameters:
| Parameter | Description |
| –psm N | Page segmentation mode (0-13) |
| –oem N | OCR Engine Mode (0: Legacy, 1: LSTM only, 2: Legacy + LSTM, 3: Default) |
| -l LANG | Specify language (e.g., ‘eng’, ‘hin’) |
| –dpi N | Set DPI for better accuracy |
| –tessdata-dir PATH | Specify custom Tesseract data directory |
| -c VAR=VALUE | Set specific configuration variables |
Example usage:
custom_config = r'--psm 6 --oem 3 -c tessedit_char_whitelist=ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789'
text = pytesseract.image_to_string(image, config=custom_config)
EasyOCR Parameters
EasyOCR provides options to control model behavior:
| Parameter | Description |
| lang_list | List of languages to use (e.g., [‘en’, ‘hi’]) |
| gpu | Use GPU for faster inference (default: False) |
| detail | 0 for text only, 1 for bounding box & confidence, 2 for more details |
| batch_size | Number of images processed at once (higher for better performance) |
| contrast_ths | Contrast threshold for filtering text regions |
| adjust_contrast | Auto-adjust contrast for better accuracy |
| slope_ths | Threshold for detecting slanted text |
| decoder | Defines the decoding method for OCR (default: ‘greedy’, alternative: ‘beamsearch’) |
4. Conclusion
If you need a free, open-source OCR tool that works well with printed text, choose Tesseract.
If you need faster and more robust OCR, especially for handwritten text and noisy images, go for EasyOCR.
If you need enterprise-level OCR with custom models and real-time API support, ArivElm is the best choice for businesses.
For the best results, consider combining these tools: use Tesseract for structured, printed text, EasyOCR for handwritten text, and ArivElm for business-critical applications.
Do you have experience with these OCR tools? Share your thoughts in the comments!